Negative or Net suppression/reciprocal or cooperativa suppression in mediated or PLS- SEM models

The negative sign in the path  or weight means “negative or net suppression”. This is a common issue when using several variables correlated in the same model. The tricky issue is that all variables are positively related wth SC-Ad (se latent variable correlations in 2nd order HOC model), but you can observe a negative value in the path. How can this be possible? It is well documented in mediation analysis (i.e., Ato & Vallejo, 2011 page 558), and it is explained by the relative “impact” of the predictors on the dependent variable. The predictor less correlated with the dependent variable is used to “compensate” the “inflate” paths for the other predictors. The negative or net suppression occurs when all the variables have a high positive correlation among themselves (rXY, rXZ, rZY > 0), but the regression coefficient of one of the variables is negative. Reciprocal or cooperative suppression occurs when two variables are negatively correlated with each other, but both are positively correlated with the outcome variable.

Inconsistent Mediation (from Mediation (David A. Kenny) (

"If c' were opposite in sign to ab something that MacKinnon, Fairchild, and Fritz (2007) refer to as inconsistent mediation, then it could be the case that Step 1 would not be met, but there is still mediation. In this case the mediator acts like a suppressor variable. One example of inconsistent mediation is the relationship between stress and mood as mediated by coping. Presumably, the direct effect is negative: more stress, the worse the mood. However, likely the effect of stress on coping is positive (more stress, more coping) and the effect of coping on mood is positive (more coping, better mood), making the indirect effect positive. The total effect of stress on mood then is likely to be very small because the direct and indirect effects will tend to cancel each other out. Note too that with inconsistent mediation that typically the direct effect is even larger than the total effect."


Ato, M., & Vallejo, G. (2011). Los efectos de terceras variables en la investigación psicológica. Anales de Psicología, 27(2), 550-561.


Conger, A. J. (2016). A Revised Definition for Suppressor Variables: a Guide To Their Identification and Interpretation. Educational and Psychological Measurement, 34(1), 35-46.
Gaylord-Harden, N. K., Cunningham, J. A., Holmbeck, G. N., & Grant, K. E. (2010). Suppressor effects in coping research with African American adolescents from low-income communities. J Consult Clin Psychol, 78(6), 843-855.
Krus, D. J., & Wilkinson, S. M. (1986). Demonstration of properties of a suppressor variable. Behavior Research Methods, Instruments, & Computers, 18(1), 21-24.
MacKinnon, D. P., Krull, J. L., & Lockwood, C. M. (2000). Equivalence of the Mediation, Confounding and Suppression Effect. Prevention Science, 1(4), 173-181.

Visitas: 26